Bowen Ratio Research Articles

A Bowen ratio-informed method for coordinating the estimates of air-sea turbulent heat fluxes

Abstract Accurate quantification of turbulent heat fluxes [THF, comprising sensible heat flux (SHF) and latent heat flux (LHF)] and Bowen ratio (β, ratio of SHF and LHF) is essential for understanding the air-sea interaction. However, the biased estimates of SHF and LHF by widely applied bulk aerodynamic models, and the separate estimates of SHF and LHF by data-driven models, both may result in unrealistic β estimates. This study for the first time innovatively proposes a Bowen ratio-informed data-driven model (BrTHF) for coordinating the estimations of THF and β using the multivariate random forest technique and a combination of eddy covariance flux observations and meteorological and oceanic observations collected from 53 historical cruises. The result shows that the BrTHF model could not only achieve high-accuracy SHF and LHF estimates, but also avoid the outliers of β estimates that were commonly found in un-synergistic random forest and well-known COARE3.5 models.

Numerical investigation on boiling crisis characteristic of a 7-rod HCF assembly in hexagonal lattice

Helical cruciform fuel (HCF) has the advantages of larger heat transfer area, enhanced coolant mixing and self-supporting, which contribute to increasing power density and safety margins. Compared with the square lattice configuration, the hexagonal arrangement of HCF assembly is more compact, which can help achieve a higher power density. In this paper, the flow characteristics and heat transfer behaviors of HCF in hexagonal lattice were predicted at high and low vapor quality during boiling crisis based on Eulerian two-fluid model. The influence of twist pitches and cross-sections of the fuel rod on heat transfer efficiency and fuel temperature was also studied. The cross-flow intensity changed periodically with a 30° cycle at low vapor quality, and did not fluctuate periodically at high vapor quality, which decreased with the increase of flow resistance. The highest heat flux of HCF rod was the at the blade root and the lowest was at the blade tip, and the maximum to average heat flux ratio was about 1.8. The peak vapor fraction and temperature occurred at leeside side of the fuel rods. The increase of the twist pitch reduced the critical heat flux (CHF), and the increase of blade length enhanced the non-uniformity of heat flux distribution. During boiling crisis, the maximum temperature of the fuel was lower than the phase transition temperature of U-50 wt%Zr alloy, which means the cladding meltdown caused by boiling crisis will occur before phase transition of the fuel.

Estimating Phase Transition Rates in Shallow Cumulus Clouds from Mass Flux. Part II: Vertically dependent formulation

Abstract This work continued the investigation of the relationship between phase transition rates and mass flux in trade wind cumulus clouds. The latter were simulated by an LES model initialized with soundings from the RICO field project. In Part I (Kogan, 2022) we demonstrated that a very high correlation exists between integral phase transition rates and upward mass flux. In this study we focused on the vertically dependent variables and showed that a similar high correlation exists between the condensation rate 𝒞 (z) and the upward mass flux ℳ (z). Based on condensation theory, we showed that under quasi-steady approximation condensation rates can be calculated by a linear function of ℳ with the slope coefficient dependent only on temperature and pressure. The model data showed that the error of such approximation is less than a few tenths of a percent. The parameterization of the evaporation process is more complex, mostly because of the slow evaporation of raindrops as they fall through the cloud’s unsaturated areas. Nevertheless, it was possible to define the fraction of evaporation to condensation rate as a function of vertical coordinate z and cloud thickness H. This function can be quite accurately approximated by the 3rd order polynomials of z and H. It is suggested that proposed formulation of evaporation together with the quasi-steady formulation of condensation can serve as a parameterization of water phase transition rates in shallow cumulus clouds.

The effects of dynamic factors inside the bubble on sono-hydrogen yield: A numerical study

The formation of H2 by introducing ultrasonic waves to liquid has been widely recognized as a way to provide a clean, efficient, and reliable source of H2, known as Sono-Hydro-Gen. H2 comes from the chemical effects of ultrasonic waves (sonochemistry) caused by the growth and collapse of acoustic cavitation bubbles. In this work, the effects of dynamic parameters (i.e., bubble temperature, the amount of water vapor trapped inside the bubble, and collapse time) in the evolution of cavitation bubbles on H2 production are studied numerically. For an oxygen bubble, computational simulations are performed for the wide range of acoustic amplitudes (1.5–3 atm), ultrasonic frequencies (140–515 kHz), and ambient radii (0.25–20 μm), considering 22 reversible chemical reactions and 10 chemical species inside the bubble. The numerical results show that the amount of water vapor has a significant effect on the bubble collapse temperature. At low excitation amplitudes, the amount of water vapor is not enough to cause the bubble to form a strong collapse. Nevertheless, at high excitation amplitudes, the amount of water vapor is too much to reduce the bubble temperature. There exist optimal values of bubble temperature and amount of water vapor for H2 production. The optimal bubble temperatures are 5267, 4813, 4626, and 3856 K, corresponding to H2 productions of 4.21 × 10−18, 1.29 × 10−18, 2.61 × 10−19, and 8.48 × 10−20 mol, respectively, at ultrasonic frequencies of 140, 213, 355, and 515 kHz. No matter what the excitation parameters are, the optimal water vapor fraction is 0.78 ± 0.04 for H2 production. The obtained results of the present work can provide guidelines for H2 production in acoustic cavitation.

Exploring and closing the energy balance of eddy covariance measurements along a land use gradient in the West African Sudanian savanna

A good understanding of land-atmosphere exchange processes is essential for developing sustainable land management practices in Africa, in order to enhance food security and strengthen the resilience against climate change and extremes in this vulnerable region. In this study, we explore the energy balance closure (EBC) of three eddy covariance (EC) sites implemented along a land use gradient (pristine savanna forest, cropland, and degraded grassland) in the Sudanian savanna of West Africa. Our results show that the EBC strongly varies over the monsoon season and the EC sites. However, the best EBC is observed at the pristine site, which has the most homogenous vegetation. Thus, landscape heterogeneity seems to play an important role in the quality of the EC measurements. Moreover, we develop a novel post-closure method based on a quantile-mapping technique conditioned on monsoonal circulation patterns specifically determined for the West African Monsoon. This method is also compared to two well-established methods, the Bowen-ratio (BR) correction and a pure quantile-mapping using various bias measures. Our results show that the novel post-closure method outperforms the other methods and, therefore, leads to better elimination of the underestimation of the turbulent fluxes at the three savanna sites. In addition, specific characteristics of turbulent fluxes, like their strong diurnal cycle, are well represented by the new correction method.

Assessment of upscaling methodologies for daily crop transpiration using sap flows and two-source energy balance models in almonds under different water statuses and production systems

Abstract. Daily transpiration (Td) is crucial for both irrigation water management and increasing crop water productivity. The use of the remote-sensing-based two-source energy balance model (TSEB) has proven to be robust in estimating plant transpiration and evaporation separately for various crops. However, remote sensing models provide instantaneous estimations, and so daily upscaling approaches are needed to estimate daily fluxes. Daily upscaling methodologies have not yet been examined to upscale solely transpiration in woody crops. In this regard, this study aims to evaluate the proper image acquisition time throughout the day and four methodologies used to retrieve Td in almond trees with different production systems and water statuses. Hourly transpiration (Th) was estimated using the TSEB contextual approach (Th–TSEB) with high-resolution imagery five times during two diurnal courses. The tested methodologies were the following: the simulated evaporative fraction variable (EFsim), irradiance (Rs), reference evapotranspiration (ETo), and potential evapotranspiration (ETp). These approaches were first evaluated with in situ sap flow (T–SF) data and were then applied to the Th–TSEB. Daily T–SF showed significant differences among production systems and levels of water stress. The EFsim and ETp methods correlated better with measured T–SF and reduced the underestimation observed using the Rs and ETo methods, especially at noon in the severely water-stressed trees. However, the daily upscaling approaches applied in the TSEB (Td–TSEB) failed to detect differences between production systems. The lack of sensibility of Th–TSEB among production systems poses a challenge when estimating Td in canopies with discontinuous architectural structures. The use of ETp as a reference variable could address this issue as it incorporates various aerodynamic and radiative properties associated with different canopy architectures that influence the daily Th–SF pattern. However, more accurate ETp estimates or more advanced ETp models are needed.

Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG

Abstract. Atmospheric transport models are often used to simulate the distribution of greenhouse gases (GHGs). This can be in the context of forward modeling of tracer transport using surface–atmosphere fluxes or flux estimation through inverse modeling, whereby atmospheric tracer measurements are used in combination with simulated transport. In both of these contexts, transport errors can bias the results and should therefore be minimized. Here, we analyze transport uncertainties in the commonly used Weather Research and Forecasting (WRF) model coupled with the greenhouse gas module (WRF-GHG), enabling passive tracer transport simulation of CO2 and CH4. As a mesoscale numerical weather prediction model, WRF's transport is constrained by global meteorological fields via initialization and at the lateral boundaries of the domain of interest. These global fields were generated by assimilating various meteorological data to increase the accuracy of modeled fields. However, in limited-domain models like WRF, the winds in the center of the domain can deviate considerably from these driving fields. As the accuracy of the wind speed and direction is critical to the prediction of tracer transport, maintaining a close link to the observations across the simulation domain is desired. On the other hand, a link that is too close to the global meteorological fields can degrade performance at smaller spatial scales that are better represented by the mesoscale model. In this work, we evaluated the performance of strategies for keeping WRF's meteorology compatible with meteorological observations. To avoid the complexity of assimilating meteorological observations directly, two main strategies of coupling WRF-GHG with ERA5 meteorological reanalysis data were tested over a 2-month-long simulation over the European domain: (a) restarting the model daily with fresh initial conditions (ICs) from ERA5 and (b) nudging the atmospheric winds, temperatures, and moisture to those of ERA5 continuously throughout the simulation period, using WRF's built-in four-dimensional data assimilation (FDDA) in grid-nudging mode. Meteorological variables and simulated mole fractions of CO2 and CH4 were compared against observations to assess the performance of the different strategies. We also compared planetary boundary layer height (PBLH) with radiosonde-derived estimates. Either nudging or daily restarts similarly improved the meteorology and GHG transport in our simulations, with a small advantage of using both methods in combination. However, notable differences in soil moisture were found that accumulated over the course of the simulation when not using frequent restarts. The soil moisture drift had an impact on the simulated PBLH, presumably via changing the Bowen ratio. This is partially mitigated through nudging without requiring daily restarts, although not entirely alleviated. Soil moisture drift did not have a noticeable impact on GHG performance in our case, likely because it was dominated by other errors. However, since the PBLH is critical for accurately simulating GHG transport, we recommend transport model setups that tie soil moisture to observations. Our method of frequently re-initializing simulations with meteorological reanalysis fields proved suitable for this purpose.

Hysteresis in seasonal land-atmospheric interactions over India and its characteristics across croplands and forests

Abstract Satellite-derived Vegetation Optical Depth and Soil Moisture (SM) data reveal the critical role of the soil-vegetation continuum in storing rainwater during the Indian Summer Monsoon and supporting evapotranspiration (ET) during the dry non-monsoon season. During the non-monsoon drier period, the climatologically estimated spatial mean of ET exceeds precipitation input, a phenomenon known as the Soil-Vegetation Capacitor (SVC) effect, which is pivotal in maintaining ecosystem productivity. Notably, our analysis reveals significant variations in the capacitor period between croplands and forests, with croplands exhibiting a ~77 days longer due to dual crop seasons influenced by regional precipitation. The well-recognized hysteresis curves, observed in magnetization and soil-water characteristic curves (SWCC), highlight phenomena where a system's state is influenced by its historical inputs or states and are integral to our findings. We report a previously undocumented seasonal hysteresis in the relationship between the evaporative fraction (EVF) and SM for Indian croplands and forests. We further found that the croplands SM-EVF relation exhibits a reversal in hysteresis in the case of root-zone SM. The surface SM-EVF hysteresis is not present in forests with large root depths and reduced soil evaporation due to high canopy shading, and yet it is present for the root-zone SM. With its reversal for croplands, the newly found hysteresis must be addressed in redefining the critical SM threshold to demarcate the energy and water-limiting regimes. It should be incorporated in the land surface modeling parameterization. Additionally, we observed hysteresis in the soil moisture-gross primary productivity (SM-GPP) relationship across both land covers and soil profiles (surface and root-zone), underscoring the need to investigate such processes to consider their dynamics in future ecological and hydrological models.

Cavitating flow through a Venturi using CFD: effects of inlet and outlet pressures

Hydrodynamic cavitation is a complex physical phenomenon that appeared in hydraulic systems (pumps, turbines, valves, Venturi tubes …etc.) when the fluid pressure decreases below the saturated vapor pressure. The works carried out in this study aimed to get a better understanding of the cavitating flow phenomenon. For this, we have numerically studied a cavitating bubbly flow through a venturi nozzle. The cavitation model is selected and solved using commercial code computational fluid dynamics (CFD). The numerical results are compared to the previous experimental and numerical data.The obtained results showed that the effect of the inlet pressure (10, 7, 5 and 2 bars) and outlet pressures (6.5, 6, 5, 4, 3.5, 1.5, and 1 bars) of the Venturi on pressure, velocity of the fluid flow and the vapor fraction formation. We found that the inlet and outlet pressures of the venturi are strongly affected on the evolution of the pressure, velocity and vapor fraction formation in the cavitating flow. The results presented in this study provide insight and useful guidance to the designer of hydrodynamic cavitation devices, identifying key geometrical and physical parameters of cavitation onset and intensification that can be manipulated to achieve the desired level of cavitation flow.

Distribution and origin of higher diamondoids in the ultra-deep Paleozoic condensates of the Shunbei oilfield in the Tarim Basin, NW China

Higher diamondoids in the condensates of the Shunbei oilfield were analyzed using GC–MS. The findings indicate that the condensates in the Shunbei oilfield were subjected to a superimposed effect of secondary alterations, including biodegradation, hydrothermal alteration, evaporative fractionation, cracking, and TSR. High local concentrations of thiaadamantanes in oil may result from the interaction of H2S, derived from Cambrian TSR, with Ordovician hydrocarbons, influenced by hydrothermal activities. Comprehensive analysis shows that TSR is local and limited in Ordovician reservoirs in the Shunbei oilfield and has no significant impact on oil chemistry. Comparative studies indicate that the diamondoid concentrations in condensates from the Shunbei oilfield have not been significantly impacted by biodegradation and evaporative fractionation. Parameters related to diamantanes can effectively characterize their geochemical characteristics and secondary alteration. A multi-parameter correlation heat map suggests that higher diamondoids in the condensates of the Shunbei oilfield are not due to high thermal evolution but have been altered by hydrothermal activity. The hydrothermal activity promotes the formation of higher diamondoids in the condensate. The higher diamondoids that are formed by hydrothermal activity offer a new perspective for studying hydrothermal processes. Additionally, this aids in studying the organic-inorganic interactions of ultra-deep organic fluids with their mineralogical and aqueous environments.

The pace of change of summertime temperature extremes

Summer temperature extremes can have large impacts on humans and the biosphere, and an increase in heat extremes is one of the most visible symptoms of climate change. Multiple mechanisms have been proposed that would predict faster warming of heat extremes than typical summer days, but it is unclear whether this is occurring. Here, we show that, in both observations and historical climate model simulations, the hottest summer days have warmed at the same pace as the median globally, in each hemisphere, and in the tropics from 1959 to 2023. In contrast, the coldest summer days have warmed more slowly than the median in the global average, a signal that is not simulated in any of 262 simulations across 28 CMIP6 models. The observed stretching of the cold tail indicates that observed summertime temperatures have become more variable despite the lack of hot day amplification. The interannual variability and trend in the warming of both hot and cold extremes compared to the median can be explained from a surface energy balance perspective based on changes in net surface radiation and evaporative fraction. Tropical hot day amplification is projected to emerge in the future (2024-2099, SSP3-7.0 scenario), while Northern Hemisphere heat extremes are expected to continue to follow the median.

Characteristics and Driving Factors of Energy Balance over Different Underlying Surfaces in the Qinghai Plateau

The study of the surface energy balance characteristics of different ecosystems in the Qinghai Plateau is of great significance for a deeper understanding of land surface processes, the water cycle, and global climate change. This study aims to compare the seasonal variations in energy balance and partitioning of four typical ecosystems on the Qinghai Plateau—swamp meadows, subalpine mountain meadows, alpine shrublands, and alpine deserts. Mantel analysis and path analysis were used to explore the regulatory mechanisms of meteorological elements on energy fluxes and the Bowen ratio (β). The results showed the following: (1) Net radiation (Rn), sensible heat flux (H), and latent heat flux (LE) all exhibited a single-peak pattern of change, and the energy partitioning was closely related to the hydrothermal conditions. Swamp meadows and subalpine mountain meadows were dominated by LE throughout the year and the growing season, while H dominated in the non-growing season. Meanwhile, alpine shrublands and alpine deserts were dominated by H throughout the year. (2) β reflected the characteristics of turbulent fluxes variations and the moisture level of the underlying surface. Swamp meadows and subalpine mountain meadows were relatively moist, with the value of β all being less than 1. Alpine shrublands and deserts were comparatively arid, with the values of β all exceeding 1. The energy closure rate ranged from 48% to 90%, with better energy closure conditions observed during the growing season compared to the non-growing season. (3) Meteorological factors collectively regulated the variations in energy fluxes and its partitioning, with H and LE being primarily influenced by Rn, relative humidity (RH), and soil moisture (Ms). β was significantly affected by RH, Ms, and the saturated vapor pressure deficit (VPD). The sensitivity of the ecosystems to changes in fluxes increased with decreasing moisture, especially in alpine deserts, with Ms, VPD and RH being the most affected. Swamp meadows were significantly associated with air temperature (Ta), soil temperature (Ts), and wind speed; subalpine mountain meadows with Ta and Ts; and alpine shrublands with Ta. These results provided a basis for further analyses of the energy balance characteristics and partitioning differences of different ecosystems on the Qinghai Plateau.

Disentangling and interpreting nonlinear molecular and isotopic variations in petroleum using machine learning

Nonlinear variations in the molecular and isotopic compositions of phases in complex geosystems greatly hinder the application of geochemical proxies. This study aims to disentangle the implicit nonlinear mathematical structures embedded in geochemical datasets, effectively disaggregating overlapping geological influences that drive the intricate variations in the geochemical signatures of phases. Employing a typical hybrid petroleum system as a case study, we utilize an unsupervised machine learning algorithm to visualize the effects of source disparities and distinct evolutionary processes, such as mixing, thermal maturation, biodegradation, and evaporative fractionation, on the molecular compositions among crude oils. We further investigate the regression relationship between molecular composition and bulk δ13C signal in petroleum. Our findings reveal that by decomposing the regression model to solely reflect a specific dominant influence, the model could provide a precise geological interpretation. Accordingly, we unravel the subtle variations and underlying mechanisms of carbon isotopic fractionation in petroleum substances from different origins under the impact of maturation. Our results underscore the substantial potential of strategically applied machine learning techniques in reconstructing the geochemical evolution of complex geosystems, advocating for their broader application.

Performance and energy consumption study of a dual-evaporator loop heat pipe for chip-level cooling

The dual-evaporator loop heat pipe (DeLHP) exhibits more applications than a single-evaporator loop heat pipe in a chip-level cooling field. However, increasing the evaporators leads to a complex pipeline structure. This study focuses on developing and investigating a new parallel structure for the DeLHP. Experimental research was conducted to analyze the startup characteristics of DeLHP under single-load and dual-load conditions, and its operational characteristics under various variable power conditions. Numerical simulation was employed to analyze the fluid distribution and flow characteristics. The results indicate that heating the evaporator near the vapor pipeline achieves faster startup and more stable temperatures under a single load. Under dual loads, DeLHP exhibits a faster startup compared to a single load. When the thermal load near the vapor pipeline is greater than the load on the evaporator near the liquid pipeline, DeLHP starts faster and maintains a lower stable temperature. Under a maximum total load of 300 W, the heating surface temperature stabilizes below 80 ℃. The numerical simulation results indicate that when evaporator 1 near the liquid pipeline is individually heated, the temperatures, vapor fractions, and fluid velocities of the two evaporators are more balanced. The power usage effectiveness reaches a minimum value of 1.09 at 150 W. These research findings provide reliable and substantive support for the performance optimization of DeLHPs in practical applications.

Rootzone Soil Moisture Dynamics Using Terrestrial Water‐Energy Coupling

AbstractA lack of high‐density rootzone soil moisture (θRZ) observations limits the estimation of continental‐scale, space‐time contiguous θRZ dynamics. We derive a proxy of daily θRZ dynamics — active rootzone degree of saturation (SRZ) — by recursive low‐pass (LP) filtering of surface soil moisture (θS) within a terrestrial water‐energy coupling (WEC) framework. We estimate the LP filter parameters and WEC thresholds for the piecewise‐linear coupling between SRZ and evaporative fraction (EF) at remote sensing and field scale over the Contiguous U.S. We use θS from the Soil Moisture Active‐Passive (SMAP) satellite and 218 in‐situ stations, with EF from the Moderate Resolution Imaging Spectroradiometer. The estimated SRZ compares well against SMAP Level‐4 estimates and in‐situ θRZ, at the corresponding scale. The instantaneous hydrologic state (SRZ) vis‐à‐vis the WEC thresholds is proposed as a rootzone soil moisture stress index (SMSRZ) for near‐real‐time operational agricultural drought monitoring and agrees well with established drought metrics.

Disentangling the Impacts of Environmental Factors on Evaporative Fraction Across Climate Regimes

AbstractEvaporative fraction (EF) is a useful measure for quantifying land surface energy partitioning processes and determining evaporative regimes; however, its influencing factors remain highly uncertain. Here, global data sets were compiled to disentangle the effects of environmental variables on EF variations along climate and land surface gradients. We found that (a) at annual timescales, ecosystem‐level EF could be expressed as a power law function of aridity index. The relationships of mean annual soil water content (SWC) and leaf area index (LAI) with mean annual EF resembled the traditional evaporative regime theory; (b) at daily timescales, the boosted regression tree method quantitatively revealed that the impacts of environmental variables (including meteorological variables) on EF showed equal importance, especially at humid sites, primarily due to the different response direction and magnitude of latent heat (LE) and sensible heat (H) fluxes to environmental changes. Particularly, the contrasting responses of LE (positive) and H (negative) to SWC, LAI, and relative humidity enhanced the positive effects of those influencing variables on EF; whereas, the correlations between EF and energy‐related factors (i.e., net radiation‐Rn and air temperature‐Ta) deteriorated as both LE and H showed positive response patterns to those variables; (c) meteorological factors were also found to have nonlinear effects on daily EF, further modified by climatic conditions. Rn near 150 W/m2 and Ta near 15°C appeared to be important energy‐partitioning thresholds at drier and humid sites, respectively. Moreover, changing interactions among environmental variables with climates were demonstrated to be important for better explaining EF variations.

Evaluation of potential evapotranspiration models over fluxdata network cropland sites

Utilizing potential evapotranspiration (PET) for the estimation of actual evapotranspiration (AET) in cropland is highly valuable for determining agricultural water requirements and developing irrigation schedules. Discrepancies between anticipated and actual PET values may arise due to the limitations in previous reference standards employed for evaluation. A comprehensive evaluation of the accuracy of the PET models in cropland was conducted in this study. Non-water-stressed days with evaporation fraction (EF) exceeding the 95th percentile threshold were selected from cropland sites in the FLUXNET Tier 1 database as the basis for calibrating and validating 22 PET calculation models at the daily scale and 19 at the sub-daily scale. Results indicated that the Penman (1948), Penman (1963), and all radiation-based models showed strong performance, with R2, RMSE, and NSE of 0.82–0.89, 0.58–0.86 mm day−1, and 0.54–0.77 at the daily scale, and 0.73–0.81, 0.04–0.05 mm 0.5 h−1, and 0.62–0.72 at the sub-daily scale, respectively. Four recently developed radiation-based models have exhibited remarkable accuracy on a daily basis. The relative model errors (RMSE/MEAN) tended to decrease as net radiation (Rn), temperature (Ta), and vapor pressure deficit (VPD) increased at both daily and sub-daily time scales. The models displayed strong accuracy in estimating daily PET when Ta > 15 ℃ or 0.4 < VPD < 1.0, with RMSE/MEAN values ranging from 0.10 to 0.22 and R2 values ranging from 0.76 to 0.89. Higher accuracy in sub-daily scale PET estimates was achieved when Ta > 15 ℃ or 0.4 < VPD < 1.6, with RMSE/MEAN of 0.24–0.43 and R2 of 0.54–0.85, respectively. Additionally, the time lag between PET and Rn, Ta, and VPD increased as Rn, Ta, and VPD increased at the sub-daily scale, which may contribute to the reduced precision of sub-daily PET estimates compared to daily scale estimates. These findings suggest that PET models with calibrated parameters have the potential to serve as the basis for estimating cropland AET, and can provide direction for future model improvement.

Green Synthesis of Sulphuric Acid Based on "Geber's Method": A Detailed Aspen Plus Simulation

Sulfuric acid (H2SO4) has a wide range of applications, but its current synthesis route via the contact process negatively impacts the atmospheric environment with harmful gaseous pollutants. Thus, based on the non-random two-liquids (NRTL) thermodynamic method, this study presents a detailed Aspen Plus V8.8 simulation of the green synthesis route of H2SO4 based on Geber's method developed already in the 18th century. The research investigates the efficiency and energy dynamics of the process through the analysis of key process parameters such as reactor's heat duty, vapor fraction, and molar extent of reaction in the selected configuration, using green vitriol (FeSO4∙7H2O) as a natural raw material. This study presented a novel manufacturing route that resulted in H2SO4 of 85.76% purity (33.71 kg/h), considering the chosen parameter space. The results highlight the impact of reactant component molar yield and fractional conversion of iron (II) sulfate (FeSO4) on heat duty and the optimal molar extent for maximizing H2SO4 production in a series of equilibrium reactors. In addition, appropriate operational parameters for the synthesis process were carefully specified, offering a pathway towards sustainable and eco-friendly H2SO4 production, which should emit zero greenhouse gases. Further optimization of the reactor conditions, can help maximize the yield of H2SO4, while minimizing energy consumption and byproduct formation. Developing advanced wastewater treatment units to purify the wastewater stream containing trace amounts of H2SO4 and dissolved sulfur trioxide (SO3) can mitigate environmental impact and ensure compliance with regulatory standards.

Intercomparison of sensible and latent heat flux measurements from combined eddy covariance, energy balance, and Bowen ratio methods above a grassland prairie

We present a comparison of four different methods of measuring sensible (H) and latent (LE) heat fluxes for a year over a mixed grass prairie ecosystem in the Nebraska SandHills [eddy covariance (EC), energy balance/Bowen ratio (EBBR), residual energy (RES), modified Bowen ratio (MBR) methods]. Additionally, we developed a set of quality control criteria for each method and present a simplification to the traditional EBBR setup. Using EC as reference, all methods yielded similar estimates of yearly H (regression slopes (m) ~ 2% from unity; HEC > HEBBR, HRES, and HMBR). For yearly LE, EBBR and RES yielded similar estimates with EC (m ~ 2% from unity; LEEC < LEEBBR and LERES), while a larger bias was found from MBR (m ~ 8% from unity; LEEC > LEMBR). At shorter time scales (~ hourly), moderate scatter was found about linear regression fits for H between EBBR and EC (R2 = 0.81), with smaller scatter between RES and MBR, and EC (R2 = 0.91). For LE, smaller scatter was also measured between EC, and EBBR and RES (R2 = 0.89 and 0.87, respectively), with the larger scatter between EC and MBR (R2 = 0.65). This suggests methods other than EC may be well suited to longer-term applications (≥ yearly), but have larger uncertainty on individual measurements.

Monitoring anomalies on large-scale energy and water balance components by coupling remote sensing parameters and gridded weather data.

The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm was applied with MODIS images and gridded weather data from 2007 to 2021, to monitor the energy balance components and their anomalies, in the Atlantic Forest (AF) and Caatinga (CT) biomes inside the coastal agricultural growing zone, Northeast Brazil. Considering the long-term data, the Rn values between the biomes are not significantly different, however presenting distinct Rn partitions into latent (λE), sensible (H), and ground (G) heat fluxes between biomes. The Rn values annual averages are 9.40 ± 0.21 and 9.50 ± 0.23MJm-2 d-1, for AF and CT, respectively. However, for respectively AF and CT, they are respectively 5.10 ± 1.14MJm-2 d-1 and 4.00 ± 0.99MJm-2 d-1 for λE; 3.80 ± 1.12MJm-2 d-1 and 5.00 ± 1.00MJm-2 d-1 for H; 0.50 ± 0.12MJm-2 d-1 and 0.40 ± 0.10MJm-2 d-1 for G, yielding respective mean evaporative fraction (Ef = λE/(Rn - G) values of 0.60 ± 0.12 and 0.50 ± 0.15. Anomalies on λE, H, and Ef were detected through standardized index for these energy balance components by comparing the results for the years 2018 to 2021 with the long-term values from 2007 to each of these years, showing that the energy fluxes between surfaces and the lower atmosphere, and then the root-zone moisture conditions for both biomes, may strongly vary along seasons and years, with alternate positive and negative anomalies. These assessments are important for water policies as they can picture suitable periods and places for rainfed agriculture as well as the irrigation needs in irrigated agriculture, allowing rational agricultural environmental management while minimizing water competitions among other water users, under climate and land-use changes conditions.